Efficient linear network model for TEP based on piecewise McCormick relaxation

Abstract

This study presents a novel scheme for transmission expansion planning (TEP) based on piecewise McCormick relaxation. The model presented considers investment and operation cost and identifies the transmission lines to be built. Since the AC power flow equations are inherently non-convex and non-linear, the resulting TEP model will be a highly complex optimisation problem, in which the optimal global solution is not guaranteed to be found by the existing techniques. This study aims to transform the non-linear model of the power network into a novel linear one. The model proposed is much more precise compared with the DC approach, while the global solution is guaranteed to be found by the off-the-shelf solvers. This accurate transformation from a non-convex and non-linear AC-TEP formulation into a linear-TEP model enables the planner to get more insight into the power flow of the power system. The TEP problem is formulated as a mixed-integer linear programming problem and is solved using the efficient commercial solvers. The results of the case studies show the tractability and exactness of the proposed model as well as its superiority over the state-of-the-art schemes.